Web Security Papers
Explore a curated collection of web security papers that delve into identifying vulnerabilities in web applications through advanced techniques like fuzzing and program analysis.
Source Code: GitHub RepositoryLast Updated: Thu, 19 Jun 2025 12:18:56 GMT
| ID | Tier | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 504 | 2005 | SIGPLAN | CCF-A TH-CPL-A | 3648 | 182.40 | ||||
| 193 | 2021 | TDSC | CCF-A TH-CPL-A | 672 | 168.00 | ||||
| 253 | Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks | 2019 | NeurIPS | CCF-A TH-CPL-A | 930 | 155.00 | |||
| 354 | 2016 | NDSS | CCF-A TH-CPL-A | 1210 | 134.44 | ||||
| 163 | 2021 | TSE | TH-CPL-A | 529 | 132.25 | ||||
| 205 | 2020 | WOOT | 619 | 123.80 | |||||
| 507 | Dynamic Taint Analysis for Automatic Detection, Analysis, and SignatureGeneration of Exploits on Commodity Software | 2005 | NDSS | CCF-A TH-CPL-A | 2438 | 121.90 | |||
| 350 | 2016 | CCS | CCF-A TH-CPL-A | 1056 | 117.33 | ||||
| 203 | 2020 | CSUR | 573 | 114.60 | |||||
| 51 | Using an LLM to Help With Code Understanding | 2024 | ICSE | TH-CPL-A | 107 | 107.00 | |||
| 296 | 2018 | ASE | TH-CPL-B | 749 | 107.00 | ||||
| 327 | 2017 | CCS | CCF-A TH-CPL-A | 839 | 104.88 | Type: Survey | |||
| 476 | 2008 | NDSS | CCF-A TH-CPL-A | 1762 | 103.65 | Type: Survey | |||
| 344 | 2017 | NDSS | CCF-A TH-CPL-A | 829 | 103.63 | ||||
| 300 | 2018 | CCS | CCF-A TH-CPL-A | 719 | 102.71 | ||||
| 439 | 2011 | FSE | TH-CPL-A | 1331 | 95.07 | ||||
| 416 | 2013 | CACM | 1131 | 94.25 | |||||
| 288 | 2018 | IEEE S&P | CCF-A TH-CPL-A | 658 | 94.00 | ||||
| 513 | Search-based software test data generation: a survey | 2004 | STVR | 1945 | 92.62 | ||||
| 282 | 2019 | TSE | TH-CPL-A | 552 | 92.00 | Type: Survey | |||
| 237 | 2020 | Proceedings of the IEEE | 431 | 86.20 | |||||
| 59 | An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation | 2023 | TSE | TH-CPL-A | 167 | 83.50 | |||
| 402 | 2013 | JSS | TH-CPL-B | 959 | 79.92 | Type: Survey | |||
| 390 | Modeling and discovering vulnerabilities with code property graphs | 2014 | IEEE S&P | CCF-A TH-CPL-A | 876 | 79.64 | |||
| 304 | 2018 | Artech House | 554 | 79.14 | Type: Book | ||||
| 454 | 2010 | IEEE S&P | CCF-A TH-CPL-A | 1120 | 74.67 | ||||
| 294 | 2018 | IEEE S&P | CCF-A TH-CPL-A | 505 | 72.14 | ||||
| 30 | Large Language Model guided Protocol Fuzzing | 2024 | NDSS | CCF-A TH-CPL-A | 67 | 67.00 | Technique: Large Language Model | ||
| 157 | Automatic Inference of Search Patterns for Taint-Style Vulnerabilities | 2021 | IEEE S&P | CCF-A TH-CPL-A | 256 | 64.00 | |||
| 129 | 2022 | CSUR | 189 | 63.00 | Type: Survey | ||||
| 272 | 2019 | NDSS | CCF-A TH-CPL-A | 373 | 62.17 | ||||
| 79 | Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction | 2023 | ICSE | TH-CPL-A | 123 | 61.50 | |||
| 333 | 2017 | ASE | TH-CPL-B | 477 | 59.63 | ||||
| 489 | 2007 | Addison-Wesley | 1050 | 58.33 | Type: Book | ||||
| 342 | Software vulnerability analysis and discovery using machine-learning and data-mining techniques: A survey | 2017 | CSUR | 466 | 58.25 | ||||
| 198 | Vulnerability detection with fine-grained interpretations | 2021 | FSE | TH-CPL-A | 230 | 57.50 | |||
| 316 | 2018 | IEEE S&P | CCF-A TH-CPL-A | 392 | 56.00 | ||||
| 197 | Vuldeelocator: a deep learning-based fine-grained vulnerability detector | 2021 | TDSC | CCF-A TH-CPL-A | 223 | 55.75 | |||
| 330 | 2017 | ASE | TH-CPL-B | 443 | 55.38 | ||||
| 340 | 2017 | IEEE S&P | CCF-A TH-CPL-A | 441 | 55.13 | ||||
| 267 | 2019 | USENIX Security | CCF-A TH-CPL-A | 328 | 54.67 | ||||
| 496 | Pixy: A Static Analysis Tool for Detecting Web Application Vulnerabilities | 2006 | IEEE S&P | CCF-A TH-CPL-A | 1033 | 54.37 | |||
| 130 | 2022 | Software | 160 | 53.33 | |||||
| 521 | 1990 | CACM | 1814 | 51.83 | |||||
| 212 | Combining Graph-Based Learning With Automated Data Collection for Code Vulnerability Detection | 2020 | TIFS | CCF-A TH-CPL-A | 249 | 49.80 | |||
| 510 | Finding Security Vulnerabilities in Java Applications with Static Analysis | 2005 | USENIX Security | CCF-A TH-CPL-A | 954 | 47.70 | |||
| 355 | 2016 | IEEE S&P | CCF-A TH-CPL-A | 429 | 47.67 | ||||
| 305 | 2018 | Cybersecurity | 328 | 46.86 | Type: Survey | ||||
| 33 | 2024 | ICSE | TH-CPL-A | 46 | 46.00 | ||||
| 384 | 2014 | CCS | CCF-A TH-CPL-A | 504 | 45.82 | ||||
| 268 | NAUTILUS: Fishing for Deep Bugs with Grammars | 2019 | NDSS | CCF-A TH-CPL-A | 273 | 45.50 | |||
| 488 | Cross Site Scripting Prevention with Dynamic Data Tainting and Static Analysis | 2007 | NDSS | CCF-A TH-CPL-A | 817 | 45.39 | |||
| 501 | 2006 | SIGPLAN | CCF-A TH-CPL-A | 860 | 45.26 | ||||
| 343 | 2017 | FSE | TH-CPL-A | 360 | 45.00 | ||||
| 481 | 2008 | PLDI | TH-CPL-A | 746 | 43.88 | Type: Survey | |||
| 308 | 2018 | CCS | CCF-A TH-CPL-A | 307 | 43.86 | ||||
| 515 | Securing web application code by static analysis and runtime protection | 2004 | WWW | CCF-A TH-CPL-A | 914 | 43.52 | |||
| 280 | 2019 | ICSE | TH-CPL-A | 259 | 43.17 | ||||
| 307 | 2018 | TR | 291 | 41.57 | Type: Survey | ||||
| 278 | 2019 | TSE | TH-CPL-A | 243 | 40.50 | ||||
| 422 | 2012 | USENIX Security | CCF-A TH-CPL-A | 516 | 39.69 | ||||
| 220 | 2020 | USENIX Security | CCF-A TH-CPL-A | 196 | 39.20 | ||||
| 319 | What You Corrupt Is Not What You Crash: Challenges in Fuzzing Embedded Devices | 2018 | NDSS | CCF-A TH-CPL-A | 270 | 38.57 | |||
| 169 | 2021 | FSE | TH-CPL-A | 154 | 38.50 | ||||
| 10 | Code-Aware Prompting: A Study of Coverage-Guided Test Generation in Regression Setting using LLM | 2024 | FSE | TH-CPL-A | 38 | 38.00 | |||
| 236 | 2020 | IEEE S&P | CCF-A TH-CPL-A | 187 | 37.40 | ||||
| 5 | Automated Unit Test Improvement using Large Language Models at Meta | 2024 | FSE | TH-CPL-A | 37 | 37.00 | |||
| 463 | 2010 | IEEE S&P | CCF-A TH-CPL-A | 555 | 37.00 | ||||
| 467 | 2009 | ICSE | TH-CPL-A | 579 | 36.19 | ||||
| 274 | 2019 | ICSE | TH-CPL-A | 217 | 36.17 | Target: Web Application Target: RESTful API | |||
| 461 | 2010 | IEEE S&P | CCF-A TH-CPL-A | 523 | 34.87 | ||||
| 273 | 2019 | TOSEM | TH-CPL-A | 207 | 34.50 | ||||
| 509 | 2005 | SIGPLAN | CCF-A TH-CPL-A | 686 | 34.30 | ||||
| 484 | 2008 | IEEE S&P | CCF-A TH-CPL-A | 574 | 33.76 | ||||
| 486 | 2008 | ICSE | TH-CPL-A | 573 | 33.71 | ||||
| 271 | 2019 | IEEE S&P | CCF-A TH-CPL-A | 201 | 33.50 | ||||
| 473 | 2009 | SIGPLAN | CCF-A TH-CPL-A | 527 | 32.94 | ||||
| 289 | 2018 | arXiv | 225 | 32.14 | |||||
| 472 | 2009 | ICSE | TH-CPL-A | 507 | 31.69 | ||||
| 492 | 2007 | PLDI | TH-CPL-A | 558 | 31.00 | ||||
| 258 | 2019 | IEEE S&P | CCF-A TH-CPL-A | 181 | 30.17 | ||||
| 341 | 2017 | CCS | CCF-A TH-CPL-A | 239 | 29.88 | ||||
| 438 | DTA++: Dynamic Taint Analysis with Targeted Control-Flow Propagation | 2011 | NDSS | CCF-A TH-CPL-A | 418 | 29.86 | |||
| 276 | 2019 | ISSTA | TH-CPL-A | 177 | 29.50 | ||||
| 18 | 2024 | OOPSLA | TH-CPL-A | 29 | 29.00 | Technique: Large Language Model (LLM) | |||
| 235 | 2020 | ICST | TH-CPL-B | 145 | 29.00 | ||||
| 266 | Minemu: The World's Fastest Taint Tracker | 2019 | RAID | TH-CPL-B | 174 | 29.00 | |||
| 499 | 2006 | USENIX Security | CCF-A TH-CPL-A | 550 | 28.95 | ||||
| 391 | 2014 | USENIX Security | CCF-A TH-CPL-A | 315 | 28.64 | ||||
| 500 | Taint-Enhanced Policy Enforcement: A Practical Approach to Defeat a Wide Range of Attacks | 2006 | USENIX Security | CCF-A TH-CPL-A | 534 | 28.11 | |||
| 358 | ProTracer: Towards Practical Provenance Tracing by Alternating Between Logging and Tainting | 2016 | NDSS | CCF-A TH-CPL-A | 250 | 27.78 | |||
| 431 | 2012 | IEEE S&P | CCF-A TH-CPL-A | 356 | 27.38 | ||||
| 518 | 2003 | WWW | CCF-A TH-CPL-A | 596 | 27.09 | ||||
| 196 | 2021 | USENIX Security | CCF-A TH-CPL-A | 108 | 27.00 | ||||
| 226 | 2020 | ICSE | TH-CPL-A | 135 | 27.00 | ||||
| 230 | 2020 | NDSS | CCF-A TH-CPL-A | 128 | 25.60 | ||||
| 361 | TaintART: A Practical Multi-level Information-Flow Tracking System for Android RunTime | 2016 | CCS | CCF-A TH-CPL-A | 229 | 25.44 | |||
| 145 | 2022 | USENIX Security | CCF-A TH-CPL-A | 76 | 25.33 | ||||
| 506 | 2005 | RAID | TH-CPL-B | 502 | 25.10 | ||||
| 279 | 2019 | IoTSMS | 150 | 25.00 |
0 of 522 row(s) selected.